In this proposal we seek to design an efficient tool for large-scale investigation of an understudied genetic feature. HERV-K and SVA elements (HKLEs), which both contain a HERV-K long terminal repeat, are insertionally polymorphic, act as promoters and enhancers, and alter genome structure and epigenetics. As such, HKLEs have demonstrable effects on the function of the surrounding genome, primarily through altering cis-gene expression. These effects suggest HKLEs may contribute to the germ-line causes and somatic progression of disease. Indeed, our preliminary studies suggest that these elements are associated with multiple sclerosis and glioblastoma, additionally HKLEs have been shown to be overexpressed in a variety of complex diseases including our study of childhood acute lymphoblastic leukemia. Currently, the most effective method to measure these important genomic features is via whole genome sequencing, which is prohibitively expensive and computationally burdensome. Previous methods to enrich sequencing data for insertion breakpoints are subject to sacrifices of specificity, PCR bias, and sequence errors. We propose to develop a method, HKLE-seq, that will harness the efficiency of target enrichment methods while incorporating features that reduce error and bias. Upon development, this method will be applied to future large-scale planned studies of multiple sclerosis, glioblastoma, and childhood acute lymphoblastic leukemia. Furthermore, HKLE-seq will be available for use by researchers conducting clinical and epidemiological studies worldwide.